Model Pricing and Billing
Review multipliers, price conversion rules, standardized billing units, and model costs.
1. Billing Rules
Core billing unit: The platform bills per 100 million Tokens. A 1x multiplier = 40 yuan per 100 million Tokens, equivalent to 0.4 yuan per 1 million Tokens. The “multiplier” and “price per 1 million Tokens” columns in the table below use the same conversion basis, so you can read the prices directly from the table.
| Billing Item | Standard | Description |
|---|---|---|
| 1x multiplier | 40 yuan / 100 million Tokens | Equivalent to 0.4 yuan per 1 million Tokens and used as the base conversion standard for the price table. |
| 2x multiplier | 80 yuan / 100 million Tokens | Prices scale linearly from the base multiplier, so the price per 1 million Tokens also doubles. |
| 5x multiplier | 200 yuan / 100 million Tokens | Used for models with higher costs or resource requirements. |
| 10x multiplier | 400 yuan / 100 million Tokens | Higher-cost models use higher multipliers. See the model price table for details. |
One Key works with every model. Multipliers only represent differences in model costs. You do not need a separate Key for each model.
Actual charges are based on system records. If a model receives a temporary subsidy, promotional discount, or multiplier adjustment, the price table on this page will be updated accordingly.
2. Cache Hits
What is a cache hit? When consecutive requests contain a large amount of identical context, the system can reuse previously processed content. The cached portion does not need to be recomputed at the full input rate. Common examples include long conversations, consecutive follow-up questions, code completion, agent workflows, and multi-turn tool calls.
| Item | Billing Method | Description |
|---|---|---|
| Cached input | Usually billed at a 0.1x multiplier | The cached portion costs about 10% of standard input, reducing costs for long-context use cases. |
| Uncached input | Billed at the model's corresponding multiplier | New content and substantially changed context are billed at the normal input rate. |
| Special models / periods of instability | May be billed at a 0.2x multiplier or temporarily bypass caching | For example, cache billing may be adjusted based on actual capabilities for high-cost models or when an upstream provider is unstable. |
Example: If you ask consecutive follow-up questions in a long conversation, the repeated context carried over from earlier turns is billed at the cache multiplier when it results in a cache hit. New questions and newly generated output are still billed at the model's corresponding multiplier.
Whether a request results in a cache hit depends on the request content, model capabilities, upstream caching policy, and current system availability. Final charges are based on billing records.
3. Model List and Multiplier Price Table (All Models Available)
How to read the table: Start with the model name, then check the multiplier, and finally review the “price per 1 million Tokens.” A lower multiplier means a lower cost per Token. Multipliers and prices use the same conversion basis.
| Field | Description |
|---|---|
| Model name | The model name entered in a client, workflow, or API request. We recommend copying capitalization exactly as shown in the table. |
| Multiplier | Represents differences in model costs. Lower multipliers are better for frequent everyday use, while higher multipliers are better suited to high-value tasks. |
| Price per 1 million Tokens | Already converted using the multiplier, so you can use this column directly to estimate usage costs. |
| Temporary subsidy / promotional price | When a temporary subsidy or limited-time promotion applies, the table will show the latest multiplier. Pricing may return to its previous rate or change again when the promotion ends. |
| Provider | Display Name | Model ID | Multiplier / Billing | Price | Context | Image Capability |
|---|---|---|---|---|---|---|
| LLM API Gateway Optimization / China-Based Aggregation | Claude Sonnet 4.6 (LLM API Gateway Optimized) | claude-sonnet-4-6 | 0.5x multiplier | ¥0.2 / million Tokens | 1M | Supported |
| OpenAI | GPT-5.4 | gpt-5.4 | 2x multiplier | ¥0.8 / million Tokens | 1M | Supported |
| OpenAI | GPT-5.5 | gpt-5.5 | 4x multiplier | ¥1.6 / million Tokens | 258K | Supported |
| OpenAI / Codex | GPT-5.3 Codex Spark | gpt-5.3-codex-spark | 1x multiplier | ¥0.4 / million Tokens | 128K | Not supported |
| OpenAI | GPT Image 2 | gpt-image-2 | Per image | ¥0.05–0.10 / image | 1–2K output | Generation model |
| OpenAI | GPT Image 2 4K | gpt-image-2-4k | Per image | ¥0.5–1 / image | 4K output | Generation model |
| OpenAI | GPT-5.6 Sol | gpt-5.6-sol | 6x multiplier | ¥2.4 / million Tokens | 258K | Supported |
| OpenAI | GPT-5.6 Terra | gpt-5.6-terra | 1x multiplier | ¥0.4 / million Tokens | 258K | Supported |
| xAI / Grok | Grok 4.6 | grok-4.6 | 10x multiplier | ¥4 / million Tokens | 500K | Pending confirmation |
| xAI / Grok | Grok 4.5 | grok-4.5 | 5x multiplier | ¥2 / million Tokens | 500K | Supported |
| Anthropic | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 1x multiplier | ¥0.4 / million Tokens | 256K | Supported |
| Anthropic | Claude Sonnet 5 | claude-sonnet-5 | 10x multiplier | ¥4 / million Tokens | 1M | Supported |
| Anthropic | Claude Fable 5 | claude-fable-5 | 40x multiplier | ¥16 / million Tokens | 1M | Supported |
| Anthropic | Claude Opus 4.6 | claude-opus-4-6 | 15x multiplier | ¥6 / million Tokens | 1M | Supported |
| Anthropic | Claude Opus 4.7 | claude-opus-4-7 | 15x multiplier | ¥6 / million Tokens | 1M | Supported |
| Anthropic | Claude Opus 4.8 | claude-opus-4-8 | 15x multiplier | ¥6 / million Tokens | 1M | Supported |
| Anthropic | Claude Opus 5 | claude-opus-5 | 15x multiplier | ¥6 / million Tokens | 1M | Supported |
| Alibaba Cloud / Qwen | Qwen 3.6 Plus | qwen3.6-plus | 3x multiplier | ¥1.2 / million Tokens | 1M | Supported |
| Alibaba Cloud / Qwen | Qwen 3.7 Plus | qwen3.7-plus | 4x multiplier | ¥1.6 / million Tokens | 1M | Supported |
| Alibaba Cloud / Qwen | Qwen 3.7 Max | qwen3.7-max | 10x multiplier | ¥4 / million Tokens | 1M | Not supported |
| Alibaba Cloud / Qwen | Qwen 3.8 Max | qwen3.8-max | 20x multiplier | ¥8 / million Tokens | 1M | Supported |
| Meituan / LongCat | LongCat 2.0 | LongCat-2.0 | 1x multiplier | ¥0.4 / million Tokens | 1M | Not supported |
| Tencent Hunyuan | Hunyuan 3 | hy3 | 1x multiplier | ¥0.4 / million Tokens | 256K | Not supported |
| MiniMax | MiniMax M3 | MiniMax-M3 | 1x multiplier | ¥0.4 / million Tokens | 1M | Supported |
| MiniMax | Image 01 | image-01 | Per image | ¥0.2 / image | — | Generation model |
| MiniMax | Image 01 Live | image-01-live | Per second | ¥2 / second | — | Generation model |
| StepFun | Step 3.7 Flash | step-3.7-flash | 1x multiplier | ¥0.4 / million Tokens | 256K | Supported |
| ByteDance / Doubao | Doubao Seed 2.1 Turbo | doubao-seed-2.1-turbo | 3x multiplier | ¥1.2 / million Tokens | 128K | Supported |
| Xiaomi / MiMo | MiMo V2.5 Pro | mimo-v2.5-pro | 4x multiplier | ¥1.6 / million Tokens | 1M | Not supported |
| Xiaomi / MiMo | MiMo V2.5 | mimo-v2.5 | 2x multiplier | ¥0.8 / million Tokens | 1M | Supported |
| DeepSeek | DeepSeek V4 Pro | deepseek-v4-pro | 7.5x multiplier | ¥3 / million Tokens | 1M | Not supported |
| DeepSeek | DeepSeek V4 Flash | deepseek-v4-flash | 2.5x multiplier | ¥1 / million Tokens | 1M | Not supported |
| Moonshot AI / Kimi | Kimi K3 | kimi-k3 | 25x multiplier | ¥10 / million Tokens | 1M | Supported |
| Zhipu / Z.ai | GLM 5.1 | glm-5.1 | 5x multiplier | ¥2 / million Tokens | 256K | Supported |
| Zhipu / Z.ai | GLM 5.2 | glm-5.2 | 8x multiplier | ¥3.2 / million Tokens | 1M | Supported |
API endpoint: Use https://api.llm-token.cn/v1 whenever possible. If a client is incompatible with an address that includes /v1, try https://api.llm-token.cn instead. Different API gateway platforms, clients, and plugins may have different Base URL requirements. After switching models, we recommend testing with a small request first.
Price Table Change Monitoring Skill Installation Guide
The price table change monitoring Skill has been updated to 1.0.4. The new version fixes issues reading large tables in public Feishu documents and prioritizes the actual model price table, preventing explanatory tables from being misidentified as price tables.
| What It Does | Description |
|---|---|
| Automatically detects changes | Monitors model, multiplier, and price tables in public Feishu documents to identify added or removed models, multiplier changes, and price changes per 1 million Tokens. |
| Automatically formats notifications | Outputs a Markdown notification when changes occur, ready to send to WeChat groups, Telegram, internal company groups, or bot messages. |
| Designed for customer monitoring | Resellers, team administrators, and customer-community managers can use it to track price changes without manually opening the document and comparing tables every day. |
| Stays quiet when nothing changes | Outputs NO_REPLY when no changes are detected, making it suitable for OpenClaw, cron, or other automation tasks. |
One-command installation
clawhub install feishu-public-table-monitorUpdate an existing installation to the latest version
clawhub update feishu-public-table-monitor --forceRecommended update command for an OpenClaw / Lobster workspace
clawhub --workdir ~/.openclaw/workspace update feishu-public-table-monitor --forceExample command for monitoring this price table
Before running the command, enable public internet sharing for the target document in Feishu. Then replace PASTE_YOUR_PUBLIC_FEISHU_DOC_URL_HERE below with its public Feishu URL. Links that require sign-in cannot be monitored.
FEISHU_PUBLIC_DOC_URL='PASTE_YOUR_PUBLIC_FEISHU_DOC_URL_HERE'
python3 ~/.openclaw/workspace/skills/feishu-public-table-monitor/scripts/monitor_feishu_price_table.py \
"$FEISHU_PUBLIC_DOC_URL" \
--section-title "三、模型列表与倍率价格表(所有模型可用)"How to use it: The first run creates a baseline. Run it on a schedule after that. An output of NO_REPLY means the price table has not changed. When changes are detected, it automatically generates a notification covering added models, removed models, multiplier changes, and price changes.
Scope: This Skill is designed for publicly accessible price tables in Feishu documents. For private documents or pages that require authentication, verify access permissions and data security requirements before connecting them.